Ford rehires over 350 veteran engineers after automated AI inspection systems fail to resolve manufacturing edge cases

@rohanpaul_ai "Tribal" memory... i.e domain expertise and judgment , is hard to replicate. ( For now 😖)

@rohanpaul_ai It's failure of execution of how to implement AI or automated systems. Not failure on the tech side.

Not saying hire or fire people. From tech perspective - I stand by my statement

@rohanpaul_ai AI did not fail here because inspection is impossible. It failed because manufacturing has years of tacit knowledge hidden in edge cases, supplier mistakes, and “I’ve seen this before” judgment.

That knowledge is hard to automate until you know how to capture it.

@rohanpaul_ai I haven’t had this much fun since 1970’s UAW members used to go out and spangle their brains on various Colombian comestibles at lunchtime and did creative quality control in the afternoon…

@rohanpaul_ai Tacit knowledge doesn't transfer to a model by accident. You have to deliberately capture it first. Ford learned that the expensive way.

@rohanpaul_ai @cherylwoooo

@briansolis AI-native works when experienced people stay in the loop. Ford is a useful reminder, and a timely one.

@briansolis AI can't replace decades of instinct honed on factory floors. Ford learned what Silicon Valley keeps forgetting: experience isn't just data points. Sometimes gray beards beat algorithms because wisdom isn't programmable.

@rohanpaul_ai the rehired specialists are also expected to improve the AI training data. capturing their own tacit knowledge so Ford can try automating them away next time.

@briansolis finally someone said it out loud